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General Information
    • ISSN: 2010-3697
    • Frequency: Bimonthly
    • DOI: 10.7763/IJMO
    • Editor-in-Chief: Prof. Adrian Olaru
    • Executive Editor: Ms.Yoyo Y. Zhou
    • Abstracting/ Indexing: Engineering & Technology Digital Library, ProQuest, Crossref, Electronic Journals Library, Google Scholar, EI (INSPEC, IET).
    • E-mail ijmo@iacsitp.com
Editor-in-chief
Prof. Adrian Olaru
University Politehnica of Bucharest, Romania
I'm happy to take on the position of editor in chief of IJMO. It's a journal that shows promise of becoming a recognized journal in the area of modelling and optimization. I'll work together with the editors to help it progress.
IJMO 2012 Vol.2(5): 563-566 ISSN: 2010-3697
DOI: 10.7763/IJMO.2012.V2.183

Enrollment Forecasting for School Management System

Rabby Q. Lavilles and Mary Jane B. Arcilla

Abstract—The electronic School Management System (e-SMS) of Mindanao State University – Iligan Institute of Technology (MSU-IIT) is an information system that supports academic transactions in the university. Admission, curricula, pre-registration, registration, grading, and records management are functions supported by the system. Although these functions helped in the management of the university, enrollment planning specifically student projection is not supported resulting to problems on student complaints about course unavailability, merged courses or dissolved sections. This study explores time series models in projecting the number of students enrolled in a course as forecasting support for e-SMS. A statistical modeling method is adapted in developing the models which includes problem definition and data collection, model formulation, model verification and model implementation. Problem definition and data collection involves defining variables to be considered as well as cleaning the data. Model formulation uses time series models and graphs in analyzing patterns of data in each course. Model verification is done by comparing the result of the projection and actual enrollment while implementation explains the integration of the enrollment forecasting to the e-SMS. Experimental result yields an average of 20% difference between the forecasted and actual values. The resulting forecasts can be used to support in determining the number of sections to be opened before the enrollment commence.

Index Terms—School management system, student projection, enrollment forecasting.

The authors are with Mindanao State Univeristy – Iligan Institute of Technology, Philippines (e-mail: rabby.lavilles@g.msuiit.edu.ph).

[PDF]

Cite: Rabby Q. Lavilles and Mary Jane B. Arcilla, "Enrollment Forecasting for School Management System," International Journal of Modeling and Optimization vol. 2, no. 5, pp. 563-566, 2012.

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